Abstract

How much information with regard to identity and further individual participantcharacteristics are revealed by relatively short spatio-temporal motion trajectories of a person?We study this question by selecting a set of individual participant characteristics and analysingmotion captured trajectories of an exemplary class of familiar movements, namely handover of anobject to another person. The experiment is performed with different participants under different,predefined conditions. A selection of participant characteristics, such as the Big Five personalitytraits, gender, weight, or sportiness, are assessed and we analyse the impact of the three factor groups"participant identity", "participant characteristics", and "experimental conditions" on the observedhand trajectories. The participants' movements are recorded via optical marker-based hand motioncapture. One participant, the giver, hands over an object to the receiver. The resulting time courses ofthree-dimensional positions of markers are analysed. Multidimensional scaling is used to projecttrajectories to points in a dimension-reduced feature space. Supervised learning is also applied.We find that "participant identity" seems to have the highest correlation with the trajectories, withfactor group "experimental conditions" ranking second. On the other hand, it is not possible to find acorrelation between the "participant characteristics" and the hand trajectory features.